[3915] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[17181] | 3 | * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[3915] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System;
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[6256] | 23 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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[15406] | 24 | using HeuristicLab.MainForm;
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[5699] | 25 | using HeuristicLab.Problems.DataAnalysis.Symbolic.Views;
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[3915] | 26 |
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[5699] | 27 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression.Views {
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| 28 | public partial class InteractiveSymbolicRegressionSolutionSimplifierView : InteractiveSymbolicDataAnalysisSolutionSimplifierView {
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[5717] | 29 | public new SymbolicRegressionSolution Content {
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| 30 | get { return (SymbolicRegressionSolution)base.Content; }
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| 31 | set { base.Content = value; }
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| 32 | }
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| 33 |
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[5699] | 34 | public InteractiveSymbolicRegressionSolutionSimplifierView()
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[15406] | 35 | : base(new SymbolicRegressionSolutionImpactValuesCalculator()) {
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[5699] | 36 | InitializeComponent();
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| 37 | this.Caption = "Interactive Regression Solution Simplifier";
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[3915] | 38 | }
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| 39 |
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[5717] | 40 | protected override void UpdateModel(ISymbolicExpressionTree tree) {
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[14027] | 41 | var model = new SymbolicRegressionModel(Content.ProblemData.TargetVariable, tree, Content.Model.Interpreter, Content.Model.LowerEstimationLimit, Content.Model.UpperEstimationLimit);
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[8972] | 42 | model.Scale(Content.ProblemData);
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[5818] | 43 | Content.Model = model;
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[3915] | 44 | }
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| 45 |
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[15406] | 46 | protected override ISymbolicExpressionTree OptimizeConstants(ISymbolicExpressionTree tree, IProgress progress) {
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| 47 | const int constOptIterations = 50;
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[17057] | 48 | const int maxRepetitions = 1000;
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[15406] | 49 | var regressionProblemData = Content.ProblemData;
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[8664] | 50 | var model = Content.Model;
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[17057] | 51 | progress.CanBeStopped = true;
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| 52 | var prevResult = 0.0;
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| 53 | var result = 0.0;
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| 54 | int reps = 0;
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| 55 |
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| 56 | do {
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| 57 | prevResult = result;
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| 58 | result = SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(model.Interpreter, tree, regressionProblemData, regressionProblemData.TrainingIndices,
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| 59 | applyLinearScaling: true, maxIterations: constOptIterations, updateVariableWeights: true, lowerEstimationLimit: model.LowerEstimationLimit, upperEstimationLimit: model.UpperEstimationLimit,
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| 60 | iterationCallback: (args, func, obj) => {
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| 61 | double newProgressValue = progress.ProgressValue + 1.0 / (constOptIterations + 2); // (maxIterations + 2) iterations are reported
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| 62 | progress.ProgressValue = Math.Min(newProgressValue, 1.0);
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| 63 | });
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| 64 | reps++;
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| 65 | } while (prevResult < result && reps < maxRepetitions &&
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| 66 | progress.ProgressState != ProgressState.StopRequested &&
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| 67 | progress.ProgressState != ProgressState.CancelRequested);
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[15406] | 68 | return tree;
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[6256] | 69 | }
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[3915] | 70 | }
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| 71 | }
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